Comprehensive Computational Analysis of Protein Phenotype Changes Due to Plausible Deleterious Variants of Human SPTLC1 Gene

Genetic variations found in the coding and non-coding regions of a geneare known to influence the structure as well as the function of proteins. Serine palmitoyltransferase long chain subunit 1 a member of α-oxoamine synthase family is encoded by SPTLC1 gene which is a subunit of enzyme serine palmitoyltransferase (SPT). Mutations in SPTLC1 have been associated with hereditary sensory and autonomic neuropathy type I (HSAN-I). The exact mechanism through which these mutations elicit protein phenotype changes in terms of structure, stability and interaction with other molecules is unknown. Thus, we aimed to perform a comprehensive computational analysis of single nucleotide polymorphisms (SNPs) of SPTLC1 to prioritize a list of potential deleterious SNPs and to investigate the protein phenotype change due to functional polymorphisms. In this study, a diverse set of SPTLC1 SNPs were collected and scrutinized to categorize the potential deleterious variants. Our study concordantly identified 21 non- synonymous SNPs as pathogenic and deleterious that might induce alterations in protein structure, flexibility and stability. Moreover, evaluation of frameshift, 3’ and 5’ UTR variants shows c.*1302T> Gas effective. This comprehensive in silico analysis of systematically characterized list of potential deleterious variants could open avenues as primary filter to substantiate plausible pathogenic structural and functional impact of variants.

pathway is required for various normal cellular functions including the survival of adipocyte cells.
The decreased de novo sphingolipid biosynthesis inside adipocytes leads to adipocyte death, adipose tissue remodeling, and metabolic disorder (4).
An important SPT subunit, SPT long chain subunit 1 encoded by SPTLC1 gene is the member of α-oxoamine synthase family (5). It is mapped to chromosome 9q22.1-q22. 3, and contains 15 exons that encode for a protein with 473 amino acid residues (6). The structure and function of SPT is usually disturbed by mutations in SPTLC1 gene, which occur at amino acids that are highly conserved throughout various species (7). p.V144D mutant lymphoblasts (14)(15)(16). Notably, identified changes also exhibited in the p.C133W and p.C133Y mutations (17).
During recent years, there has been extensive consideration in associating the genetic variations to protein phenotype changes. However, determining the disease-associated missense mutations had been a challenging task for genetic disorder research. Owing to the significance of

Indels, frameshift and UTR variants analysis
The detrimental nature of insertions, deletions and frameshift mutations were predicted by SIFT Indel Classifier that requires comma separated list of chromosome coordinates, orientation (1, -1) and indels as input (28). Functionally important indels were also filtered by PROVEAN. The indels were considered deleterious if the score was <=-2.5 and neutral if the variant score was > -2.5 (25,26).

Analysis of protein characteristics properties
MUpro server was used to find out the effect of non-synonymous SNPs (nsSNPs) on protein stability. The predicted score less than 0 shows decrease in protein stability due to the mutation; contrariwise, a score greater than 0 refers to an increase in protein stability (39). Solvent accessibility of structures was predicted by an artificial neural network-based program NetSurfP-1.1 (40) and Predict Protein (41). For approximating residue specific quality of protein structure prediction and the inherent B-factor profile of all residues along the chain by combining local structure assembly variations with sequence-and structure-based profilingResQ server was used (42).

Functional analysis of mutations
Multi-scale binding pockets on SPTLC1 protein surface were explored by GHECOM 1.0: Grid-based HECOMi finder server (43 (46).

Mutation spectrum of SPTLC1 gene
The

Indel, frameshift and UTR variants analysis
A total of 94 UTR variants were identified.

Protein characteristic properties analysis
In our analysis, PredictProtein predicted that most of the residues were in buried region (Fig. 3A).
Thus, we employed NetSurfP server. Most of the identified mutant residues belonged to the buried region of protein (Table 5) except Ser331.
Moreover, the estimated local quality defined as the distance deviation between native and model protein residual position using support vector regression showed that most of the residues were below the cut-off value (Fig. 3B). The stability and flexibility of different parts of the model evaluated by ResQ server depicted that most of the residues belonged to the well-order structure of the protein as the calculated raw and normalized beta factor values were less than the cut-off score ( Fig. 3C and Table 5). It has been observed that the mutated residues belonged to the serine Cpalmitoyltransferase activity domain (Fig. 4A).
Also, structural difference of amino acids revealed that substituted residues have explicit properties like size, shape, density and charges (Fig. 4B), thus would impact the stability and interaction with other molecules

Functional analysis of mutations
To elucidate the protein function and its association with other molecules, protein network analysis and interaction pattern has opened the avenues. Top 5 binding pockets predicted by GHECOM were graphically represented in Fig.5A.

Protein-protein network and interaction analysis
The STRING database exhibited 10 functional partners of SPTLC1, among which 8 were found with the confidence score >0.9 and two with score >0.99 ( Fig. 5B and Table 6). Predicted interaction network has demonstrated that SPTLC2 and SPTLC3 were the strongest interaction partners with highest score (c ≥ 0.99) ( Fig. 5B and Table 6) and were shown to be involved in heterodimer formation with SPTLC1 protein. We pursued our analysis to investigate the SPTLC1 protein interaction upon binding to SPTLC2. Interacting residues of SPTLC1 with SPTLC2 protein are illustrated in Fig. 6.    Study has also revealed the importance of diseasecausing mutations in the active site of SPT that alters the relative positions of hydrophobic residues of both SPTLC1 and SPTLC2 subunits at dimer interface, thus affecting the enzyme activity (9,60).
Hence, it is certainly estimated that the enzymatic action of SPT would be influenced by the mutations either through the allosteric property of protein or the disturbance in the geometry of key residues present within the active site of enzyme that contributes in the recognition of substrate, or through the inadequate dimerization of the SPT monomers (61). It has been reported that in p.C133W, p.C133CY and p.V144D model, these amino acid residues do not specifically interact with the coenzyme or the substrate but lie at two closures of the loop that contact the other monomer to retain the dimer structure (61). Our study also shows that these selected residues also do not directly contact with SPTLC2 protein, but may be present around the interacting residues (Fig. 6). We believe that in future our provided prioritized list of potentially deleterious variants will be helpful for determine the contribution of key SNPs in disease progression.